The devil’s in the data: Identifying the groups that won the election for Trump

What can audience data tell you about Trump’s supporters? Why did he resonate with them? What can marketers learn from this?

The 2016 US presidential election was arguably the world’s biggest story last year, with the manner in which it was conducted almost as big a story. Hillary Clinton hired a team which grew to over 800 people working specifically on her campaign, and which spent $332M on advertising, dwarfing her victorious rival’s spend. Donald Trump’s victory came despite only spending $18M on advertising, with a campaign team that consisted of 80 people in August, and didn’t grow far past 100. Yet his controversial messages and brash style connected with substantial swathes of the population, to the great surprise of almost all pollsters.

In 2012, Barack Obama’s 50-strong analytics team executed its data-led strategy from “The Cave”, within the campaign team’s Chicago headquarters. The team identified and activated voters by creating the perfect cycle of microtargeting models, directing volunteers to conversations with specific voters at the door or over the phone.

During the 2016 elections, data was still a key battlefield and exploiting it would reap substantial rewards. To help understand the outcome, we ask: how did each team use their data, and did it have anything to do with the result?

How they defined their audience

Clinton Clinton started from a database of Democratic voters, supporters and sympathizers, and measured them periodically from several sources (such as voter registration, voting intention, etc.) which were based on various polls.

Her team attempted to persuade voters to be more active through a branding campaign about Clinton which ran in every kind of media. Her team organised its strategy around an algorithm that showed, for example, when to show the celebrities and public figures that endorsed her message or her campaign messages.

Trump It was already known that Trump knows how to get a reaction on social media: years as a reality TV star and public figure meant that he knew how to energise a crowd whether they like or dislike him. A single link tweeted by Trump gets an average of 84,000 clicks, and when he tweeted his displeasure at Nordstrom dropping his daughter’s clothing range it gave them a follower boost of 23,115 in just 36 hours. Demonstrated here, where we monitored their profile in the Audiense Connection Platform.

Nordstrom’s follower count before and after Trump’s Tweet about them. He did say he would help businesses…

But Team Trump used more than bluster alone: during the election it created its own custom database, comprising detailed identity profiles on 220 million Americans. ‘Project Alamo’ powered a digital engagement strategy which analyzed the electorate to create a ‘psychographic’ profile of every voter, based on socio-demographic and consumer data (such as who people like or dislike, magazine subscriptions, club memberships etc.) This allowed his team to identify where specific types of audiences were, and what motivates them to act.

Most of his budget was spent on digital paid media, entrusting the media coverage to spread his messages organically. His team’s main objectives were to:

shrink the number of Clinton voters, specifically targeting groups with material designed to turn them off Hillary

earn loyalty from new, active Republicans

double-down on very short messages that fit these audiences perfectly: “Donald Trump is not your typical Republican candidate”

Who were the main Trump supporters?

This strategy requires accurate identification each group of voters, knowing how to find them, and understanding the message that will resonate with them. At such scale, of course, this can only be done using digital data.

To see how this might be done, we used a psychographic approach based on audiences of Trump supporters in order to analyze the sort of people he was connecting with, as well as seeing what personality factors his team appealed to in order to connect with them.

To analyze his super fans, we identified people in the US who indicated at least three times in a two-week period on Twitter that they were supporters of Donald Trump. We monitored for this in mid-October 2016, in the run up to the election in early November.

From the resulting audience of 17,500, we distinguished four distinct groups among his supporters.

Among this audience, four distinct clusters emerge…

Despite exhibiting different affinities and backgrounds, all of these groups displayed some common characteristics when we analyzed them in the Audiense Connection Platform using the Personality Insights capabilities powered by IBM Watson.

they have a high level of openness in their personality (emotion, adventurousness, curiosity), combined with strong levels of extroversion and low levels of agreeableness.

their needs are many; they desire a sense of community, they are highly home/family orientated, and seek ambitious challenges.

what they do not seek as much as other audiences is hedonism and, interestingly enough, a traditionally conservative mindset.

The Big Five personality traits of Trump’s supporters compared to the average US citizen. Each of these can be further segmented into psychological subsections.

We also discovered:

on the television, they never miss their favourite NFL teams, and are much more likely to watch Sean Hannity or Megyn Kelly on Fox;

they have a strong distrust of the media, but are more likely than the general population to engage with it;

their favourite TV genres are sports, chat shows, and reality TV;

they’re also very active in the digital world, with Wednesdays and Thursdays being the most popular days for them to post online, especially in the evenings.

60% of their online activity is on mobile, which is slightly lower than the rest of the US (ComScore).

So what about the unique characteristics of the subsections of his supporters? We were able to identify the following unique traits for these niches:

1) Veteran community

This was the group with the largest percentage of males, with John or Michael being the most common names. They greatly over-indexed in the Atlanta and Houston areas, and were likely to have larger-than-average followings which interact with them frequently.

Arlen Williams and Linda Suhler are two profiles that were noticeably popular among this audience. Out of the niches, this was the one whose ‘members’ respond most to news about science and technology.

This segment ranked lower for hedonism than the other groups, and messages that connected well with them focused on themes of strong leadership for the country, plus the reduction of taxes.

2) FOX News viewers

This segment was actually the least likely to follow Trump on social media, but was the most likely to react to his social posts. An evenly mixed audience in terms of gender, David and Joan are the most frequently occurring names. They are very open and post about being parents a lot more than others, as well as frequently tweeting FOX News presenters.

FOX News viewers tend to follow the entire Trump family on Twitter, and the sports broadcaster Erin Andrews is one of their favourite names on FOX. Perhaps surprisingly, Russell Brand is another popular celebrity among this audience, while Samsung is the most followed brand.

This group is highly likely to respond on social media, so any message that fitted with their values was likely to get a high amount of amplification. Key characteristics they look for in such messages are a focus on liberty and escapism, or being well-organised and presentable.

3) The #MAGA group

This segment comprises Twitter account holders that vocally identified with Trump’s Make America Great Again campaign. Surprisingly, Obama stronghold Chicago was overly represented among this group (despite Clinton winning comfortably in that area). Twitter users in this group obtained a generally high following thanks to an energised engagement with Trump’s election campaign.

This group was substantially more likely than the general population to be followers of anyone who had participated in Trump’s campaign, such as Kellyanne Conway or Mike Pence. This audiences used language that suggested messages of protection over others that they cared about was of importance to them, which was a key theme of the campaign.

4) Female Trump supporters

The smallest noteworthy, identifiable group we uncovered were the female Trump supporters. Generally, they are married and proud. They’re hooked to their phones and listen to a lot more talk radio than most people. This group displays higher levels of hedonism than the other Trump-supporting groups, and were more receptive to ideas of freedom and curiosity than the general population.

What can marketers learn from this?

Sometimes when we look through audience data in the Audiense Connection Platform, surprises crop up. But on this occasion we saw a lot of things that tallied with frequently made observations about these groups. This is a highly positive outcome, as it demonstrates the reliability of the data collected. We have produced this analysis after the event using Twitter data, Team Trump used technology in real-time, to look forward – and to strategize and execute accordingly. Despite what many predicted, it worked.

Since winning an election is reasonably analogous with conducting a marketing campaign, the lesson for marketers is wonderfully clear and unarguable: being able to find, understand and engage with audiences is a vital part of a successful marketing strategy. Not just the technical connection part, but knowing what kind of audiences you’re in a strong position to win over, and what messages are going to resonate with them.

“But, Audiense, I voted for Trump and this picture is nothing like me”

This Twitter analysis study was conducted across an audience of thousands of public Twitter profiles, and looked for patterns across large groups. As with any study of an audience this size, there will be individuals who do not align with the results, or do not fit into any of the groups.